Tan explains his step-by-step turnaround: strengthening the balance sheet with US government backing and investments from Jensen Huang and SoftBank, simplifying products, and benefiting from surging CPU demand driven by agentic AI where CPUs outperform GPUs for reinforcement learning and agent orchestration.
transcript
Lip-Bu Tan: And then first step for me is to strengthen my balance sheets. And the balance sheet is really horrible in some way. So I'm delighted, you know, US government become a big shareholder. Just I explained to President Trump, TSMC, when they started, they have the Taiwan government as a shareholder. If you look at Japan, you look at Singapore, this is the infrastructure US government get to provide the support. Secondly, very happy that Jensen Huang, my all-time friend, he also put 5 billion in investing and support me. And I'm glad I at least do some good work. His 5 billion become 25 billion now or more. And then the other part is SoftBank Masa. I used to be at SoftBank board, and then he lent a hand to help me. So we strengthened the balance sheet and then focused on the products. And I really simplified the product, listened to the customer, and then drive the next generation leadership products. And then in some ways, very lucky. Right now, the authentic AI and influence CPO become highly in demand. And so versus 1 to 8 in the training CPU to GPU, now I can see 1 to 4, maybe 1 to 1, and I'm delighted CPU become important. I talked to some of the AI model and developer, and they said, well, in term of reinforced learning, in term of the speed of orchestrating all the agents, and turn out the CPU is actually better.